Intelligent Foreign Particle Inspection Machine for Injection Liquid Examination Based on Modified Pulse-Coupled Neural Networks

• Main Authors: BoWen Zhou, YaoNan Wang, Ji Ge, Hui Zhang
• Format: Article
• Language: English
• Published: MDPI AG 2009-05-01
• Series: Sensors
• Subjects: Intelligent inspection machine; foreign particle detection; modified PCNN; injection quality inspection; image processing; illumination styles
• Online Access: http://www.mdpi.com/1424-8220/9/5/3386/

A biologically inspired spiking neural network model, called pulse-coupled neural networks (PCNN), has been applied in an automatic inspection machine to detect visible foreign particles intermingled in glucose or sodium chloride injection liquids. Proper mechanisms and improved spin/stop techniques are proposed to avoid the appearance of air bubbles, which increases the algorithms’ complexity. Modified PCNN is adopted to segment the difference images, judging the existence of foreign particles according to the continuity and smoothness properties of their moving traces. Preliminarily experimental results indicate that the inspection machine can detect the visible foreign particles effectively and the detection speed, accuracy and correct detection rate also satisfying the needs of medicine preparation.